Modern software development is evolving away from the client-server model toward network-based processing systems that provide access to data and services via the Internet or other networks. In contrast to traditional systems that host networked applications on dedicated server hardware, a “cloud” computing model allows applications to be provided over the network “as a service” supplied by an infrastructure provider. The infrastructure provider typically abstracts the underlying hardware and other resources used to deliver a customer-developed application so that the customer no longer needs to operate and support dedicated server hardware. The cloud computing model can often provide substantial cost savings to the customer over the life of the application because the customer no longer needs to provide dedicated network infrastructure, electrical and temperature controls, physical security and other logistics in support of dedicated server hardware.
Multi-tenant cloud-based architectures have been developed to improve collaboration, integration, and community-based cooperation between customer tenants without sacrificing data security. Generally speaking, multi-tenancy refers to a system where a single hardware and software platform simultaneously supports multiple user groups (also referred to as “organizations” or “tenants”) from a common data storage element (also referred to as a “multi-tenant database”). The multi-tenant design provides a number of advantages over conventional server virtualization systems. First, the multi-tenant platform operator can often make improvements to the platform based upon collective information from the entire tenant community. Additionally, because all users in the multi-tenant environment execute applications within a common processing space, it is relatively easy to grant or deny access to specific sets of data for any user within the multi-tenant platform, thereby improving collaboration and integration between applications and the data managed by the various applications. The multi-tenant architecture therefore allows convenient and cost effective sharing of similar application features between multiple sets of users.
Robust systems and applications for measuring and analyzing social media content metrics have been developed for use in the multi-tenant environment. Presently known analytics applications, such as the Radian6 system, gather metrics around blog posts, forum posts, video posts, and other social media points of interest. Relevant metrics include the number of public comments, the number of unique commenter names, number of views, and comment date. Several challenges accompany the gathering of metrics, including the endless variety of HTML page styles and the frequency with which changes occur to these pages. In the past the Radian6 system has employed a code-based approach to retrieving metrics, using a specific custom software adapter for each website under inspection.
In this regime custom adapters were configured as a Java class written to locate metrics on HTML pages. In addition to accomodating the unique stylization of each individual web page, the adapter must keep pace with page changes. What might work one day may not work the next day if the page's host or author changes the HTML design or migrates to another source. In order to track changes to a web page's HTML code, the adapter code base must be frequently updated. Because the Radian6 system covers thousands of feeds, translating to millions of posts, a Service Patch approach to updating custom adapters has been employed. However, this approach involves significant administrative overhead for the adapter developer, often requiring several days to qualify and stage the new code, and push the code changes to the appropriate servers.
Systems and methods are thus needed for retrieving metrics in a social media environment which avoid the latency associated with updating presently known custom adapters.